Self-contained code chunk for plotly graphic marking: - made a self-contained code chunk according to instructions provided by teaching team in an internal issue discussion
suppressPackageStartupMessages(library(gapminder))
suppressPackageStartupMessages(library(tidyverse))
suppressPackageStartupMessages(library(plotly))
suppressPackageStartupMessages(library(viridis))
suppressPackageStartupMessages(library(scales))
suppressPackageStartupMessages(library(RColorBrewer))
oil_consumption = read_csv(file ="Oil_Consumption_per_capita.csv")
## Parsed with column specification:
## cols(
## .default = col_double(),
## `Oil Consumption per capita (tonnes per year)` = col_character()
## )
## See spec(...) for full column specifications.
oil_consumption_2007 = oil_consumption %>%
select(`Oil Consumption per capita (tonnes per year)`, "2007") %>%
mutate(country = `Oil Consumption per capita (tonnes per year)`,
tonnes_per_capita_2007 = `2007`) %>%
select(country, tonnes_per_capita_2007)
gapminder_2007 = gapminder %>%
filter (year == "2007") %>%
select(country = "country", pop, gdpPercap, continent, lifeExp)
gapminder_oil_2007 = left_join(gapminder_2007, oil_consumption_2007, by= "country") %>%
na.omit()
## Warning: Column `country` joining factor and character vector, coercing
## into character vector
plot_oilvsgdp = gapminder_oil_2007 %>%
ggplot(aes(gdpPercap, tonnes_per_capita_2007)) +
geom_point(aes(colour = pop)) +
scale_x_log10(labels = dollar_format())+
scale_colour_distiller(
trans="log10",
breaks = 10^(0:9),
labels = comma_format(),
palette = "YlOrRd"
) +
scale_y_continuous(breaks = c(0,2,4,6,8,10))+
theme_bw()+
ggtitle("Tonnes of Oil per Capita by GDP per Capita ")
ggplotly(plot_oilvsgdp)